Stanford University · Course
Model Development, Deployment, and Ethical Considerations (XMLPH210)
Model Development, Deployment, and Ethical Considerations (XMLPH210) is a self-paced Stanford Medicine online course on machine learning in medicine: predictive modelling, deep learning on electronic health records, deployment and the ethics and liabilities of putting models into care.
Who it suits
- Clinicians and data professionals who build or evaluate healthcare models.
- People working toward the Applications of Machine Learning in Medicine Program.
What it covers
- Machine learning basics applied to clinical data, and predictive analysis.
- Deep learning with neural networks and applying models to electronic health records.
- Unsupervised learning and feature engineering.
- The utility, ethics and liabilities of deploying machine learning in healthcare.
Common questions about Model Development, Deployment, and Ethical Considerations (XMLPH210)
- How long is it?
- Stanford lists 10 hours, 100% online and on demand, with a Record of Completion.
- Is there CME credit?
- Stanford lists 10 CME credits; check its page for the terms.
- Which programme is it in?
- The Applications of Machine Learning in Medicine Program.
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Where this comes from
Written from Stanford University’s own pages, read on 2026-10-14. Content, prices and availability change, so the provider’s page is the source. We are not affiliated with Stanford University and this is not an endorsement.